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Record W4387079765 · doi:10.1007/s11356-023-29866-y

Understanding the phenomenon of saltwater intrusion sourced from desalination plants at coastal aquifers

2023· article· en· W4387079765 on OpenAlexaff
Farhat Abbas, Salem Al-Naemi, Aitazaz A. Farooque, Michael J. Phillips, Derek A. Rose

Bibliographic record

VenueEnvironmental Science and Pollution Research · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsAquiferDesalinationGroundwaterBromidePorous mediumGeologySaltwater intrusionEnvironmental scienceSoil scienceChemistryHydrology (agriculture)MineralogyGeotechnical engineeringPorosity

Abstract

fetched live from OpenAlex

Members of the Gulf Cooperation Council countries Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates rely on desalination to produce water for domestic use. Desalination produces brine that may intrude into the aquifers to pollute the fresh groundwater because of the concentration gradient and groundwater pumping. Modeling the trends of saltwater intrusion needs theoretical understanding and thorough logical experimentation. The objective of this exercise was to understand the phenomenon of saltwater intrusion using an existing set of data analyzed with the convective-diffusion equation and the two-region mobile-immobile solution model. The objective was achieved by optimizing non-measurable solute transport parameters from an existing set of data generated from a series of logical miscible displacements of potassium bromide through sepiolite minerals and curve-fitting simulations. Assumptions included that solute displacements through sepiolite porous media and the related simulations represented the phenomenon of saltwater intrusion under non-equilibrium conditions of porous media mimicking the aquifers. Miscible displacements of potassium bromide were observed from a column of 2.0-2.8 mm aggregates of sepiolite over 4 ranges of concentration and at 11 displacement speeds under saturated vertical flow deionized water and vice versa. Breakthrough curves of both bromide and potassium ions were analyzed by a curve-fitting technique to optimize transport parameters assuming solute movement was governed (i) by the convective-diffusion equation and (ii) the two-region mobile-immobile solution model. Column Peclet numbers from the two analyses were identical for potassium ions but those for bromide ions were c. 60% greater from the two-region model than from the convective-diffusion equation. For the two-region model, dispersion coefficients were well defined and remained unchanged from the convective-diffusion equation for potassium ions but decreased for bromide ions. Retardation factors for bromide ions were approximately the same, but those for potassium ions, though > 1, were poorly defined. In order to design mitigation strategies for avoiding groundwater contamination, this study's findings may help model groundwater pollution caused by the activities of desalination of seawater, which produces concentrated liquid that intrudes into the coastal aquifer through miscible displacement. However, robust saltwater intrusion models may be considered in future studies to confirm the results of the approach presented in this exercise. Field data on the groundwater contamination levels may be collected to compare with simulated trends drawn from the saltwater intrusion models and the curve-fitting technique used in this work. A comparison of the output from the two types of models may help determine the right option to understand the phenomena of saltwater intrusion into coastal aquifers of various characteristics.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.101
GPT teacher head0.301
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2023
Admission routes1
Has abstractyes

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